Cellular signaling proteins are often present at low abundance within cells and therefore are difficult to quantitate reliably in single cells. For example, protein phosphorylation is one of the most ubiquitous and vital signaling processes; however, phosphoactivated proteins can exist at extremely low levels in single cells [1-3]. Moreover, many therapeutic compounds, such as kinase inhibitors, target and inhibit protein signaling [4-9], further decreasing the endogenous levels of signaling molecules, and posing additional challenges to detecting signaling molecules in single cells. Individual cells in a population are believed to contain differing levels of signaling molecules. Such cellular signaling heterogeneity may hold important keys to understanding the degree of effectiveness of some therapeutic treatments [10-14], as well as understanding important cell biological mechanisms, such as cellular proliferation and disease recurrence [15-19]. Thus, approaches that sensitively quantify the levels of key signaling molecules in single cells would contribute greatly to an improved characterization of disease states and a more complete assessment of therapeutic efficacy.
A technical challenge in measuring key single cell signaling states is overcoming limitations in attaining sufficient sensitivity necessary to reliably detect and quantify levels of activated signaling proteins above the background noise. Cell population-averaging techniques (e.g. immunoblotting, reverse protein arrays) boost detection sensitivity; however, such methods mask individual differences among cells. Fluorescence-activated cell sorting (FACS) is currently the method of choice for high-throughput single cell analysis and has yielded valuable insights into cellular signaling status of single cells [20-22]. However, approaches that provide increased sensitivity in the measurement of signaling activation in intact, single cells (as opposed to artifact, such as debris or aggregates), could provide important new, detailed information on subtle cellular signaling differences that has been previously overlooked [12].